The Böögg Cannot Predict Record Hot Summers

The folklore: A faster Böögg explosion means a hotter summer. The reality: Record summers (>19°C) occurred whether the Böögg took 4 minutes or 60. Correlation: r = +0.19.

TidyTuesday

Data Visualization

R Programming

2025

Exploring whether Zurich’s Sechseläuten festival tradition holds predictive power: does a faster Böögg explosion mean a hotter summer? This TidyTuesday visualization tests folklore against climate data, revealing a correlation of +0.19—the opposite direction from what tradition claims.

Author

Steven Ponce

Published

November 29, 2025

Figure 1: Scatter plot testing Swiss folklore that a faster Böögg explosion predicts a hotter summer. A dotted diagonal line shows the expected negative relationship, but the data contradicts it: record hot summers (large red points above 19°C threshold) are scattered across all burn durations from 4 to 60 minutes. The 2003 European heat wave had a fast 7-minute burn, while 2023’s record summer had a slow 57-minute burn. Correlation is +0.19, opposite to folklore’s prediction.

9. GitHub Repository

Expand for GitHub Repo

The complete code for this analysis is available in tt_2025_48.qmd.

For the full repository, click here.

10. References

Expand for References

Data Source:
- TidyTuesday 2025 Week 48: Can an exploding snowman predict the summer season?

11. Custom Functions Documentation

📦 Custom Helper Functions

This analysis uses custom functions from my personal module library for efficiency and consistency across projects.

Functions Used:

fonts.R: setup_fonts(), get_font_families() - Font management with showtext
social_icons.R: create_social_caption() - Generates formatted social media captions
image_utils.R: save_plot() - Consistent plot saving with naming conventions
base_theme.R: create_base_theme(), extend_weekly_theme(), get_theme_colors() - Custom ggplot2 themes

Why custom functions?
These utilities standardize theming, fonts, and output across all my data visualizations. The core analysis (data tidying and visualization logic) uses only standard tidyverse packages.

Source Code:
View all custom functions → GitHub: R/utils

Citation

BibTeX citation:

@online{ponce2025,
  author = {Ponce, Steven},
  title = {The {Böögg} {Cannot} {Predict} {Record} {Hot} {Summers}},
  date = {2025-11-29},
  url = {https://stevenponce.netlify.app/data_visualizations/TidyTuesday/2025/tt_2025_49.html},
  langid = {en}
}

For attribution, please cite this work as:

Ponce, Steven. 2025. “The Böögg Cannot Predict Record Hot Summers.” November 29, 2025. https://stevenponce.netlify.app/data_visualizations/TidyTuesday/2025/tt_2025_49.html.

--- title: "The Böögg Cannot Predict Record Hot Summers" subtitle: "The folklore: A faster Böögg explosion means a hotter summer. The reality: Record summers (>19°C) occurred whether the Böögg took 4 minutes or 60. Correlation: r = +0.19." description: "Exploring whether Zurich's Sechseläuten festival tradition holds predictive power: does a faster Böögg explosion mean a hotter summer? This TidyTuesday visualization tests folklore against climate data, revealing a correlation of +0.19—the opposite direction from what tradition claims." date: "2025-11-29" author: - name: "Steven Ponce" url: "https://stevenponce.netlify.app" citation: url: "https://stevenponce.netlify.app/data_visualizations/TidyTuesday/2025/tt_2025_49.html" categories: ["TidyTuesday", "Data Visualization", "R Programming", "2025"] tags: [ "Sechseläuten", "Böögg", "Swiss Folklore", "Climate Data", "Weather Prediction", "Scatter Plot", "ggplot2", "ggrepel", "Correlation Analysis", "MeteoSwiss", "Zurich" ] image: "thumbnails/tt_2025_48.png" format: html: toc: true toc-depth: 5 code-link: true code-fold: true code-tools: true code-summary: "Show code" self-contained: true editor_options: chunk_output_type: inline execute: freeze: true cache: true error: false message: false warning: false eval: true --- ![Scatter plot testing Swiss folklore that a faster Böögg explosion predicts a hotter summer. A dotted diagonal line shows the expected negative relationship, but the data contradicts it: record hot summers (large red points above 19°C threshold) are scattered across all burn durations from 4 to 60 minutes. The 2003 European heat wave had a fast 7-minute burn, while 2023's record summer had a slow 57-minute burn. Correlation is +0.19, opposite to folklore's prediction.](tt_2025_48.png){#fig-1} #### 9. GitHub Repository ::: {.callout-tip collapse="true"} ##### Expand for GitHub Repo The complete code for this analysis is available in [`tt_2025_48.qmd`](https://github.com/poncest/personal-website/blob/master/data_visualizations/TidyTuesday/2025/tt_2025_48.qmd). For the full repository, [click here](https://github.com/poncest/personal-website/). ::: #### 10. References ::: {.callout-tip collapse="true"} ##### Expand for References 1. **Data Source:** - TidyTuesday 2025 Week 48: [Can an exploding snowman predict the summer season?](https://github.com/rfordatascience/tidytuesday/blob/main/data/2025/2025-12-02/readme.md) ::: #### 11. Custom Functions Documentation ::: {.callout-note collapse="true"} ##### 📦 Custom Helper Functions This analysis uses custom functions from my personal module library for efficiency and consistency across projects. **Functions Used:** - **`fonts.R`**: `setup_fonts()`, `get_font_families()` - Font management with showtext - **`social_icons.R`**: `create_social_caption()` - Generates formatted social media captions - **`image_utils.R`**: `save_plot()` - Consistent plot saving with naming conventions - **`base_theme.R`**: `create_base_theme()`, `extend_weekly_theme()`, `get_theme_colors()` - Custom ggplot2 themes **Why custom functions?**\ These utilities standardize theming, fonts, and output across all my data visualizations. The core analysis (data tidying and visualization logic) uses only standard tidyverse packages. **Source Code:**\ View all custom functions → [GitHub: R/utils](https://github.com/poncest/personal-website/tree/master/R) :::